code: def load_model(file_name: str = "model.pkl") -> dict:
      """
      Load the save pre-trained model from file system
      Args:
              file_name (str): exact path of the target saved model
      Returns:
              built model (dict)
      """
  
      with open("outputs/rules/" + file_name, "rb") as f:
          model = pickle.load(f)
  
      # restore modules from its references
      modules = []
      for model_name in model["trees"]:
          module = functions.restoreTree(model_name)
          modules.append(module)
  
      model["trees"] = modules
  
      return model
  
file_path: chefboost/chefboost/Chefboost.py
imports: import time
  import pickle
  import os
  import json
  from typing import Optional, Dict, Any, Union
  import numpy
  import pandas
  from chefboost.commons import functions, evaluate
  from chefboost.training import Training
  from chefboost.tuning import gbm, adaboost, randomforest
  from chefboost.commons.logger import Logger
label_desc: Use image node_id 4 for calling a global function with example usage: load_model(file_name) and returns: model